Monday, October 1, 2018

Machine learning APIs for Google Cloud Platform

Google Cloud
Platform (GCP) is considered to be one of the Big 3 cloud platforms among
Microsoft Azure and AWS. GCP is widely used cloud solutions supporting AI capabilities to
design and develop smart models to turn your data into insights at a cheap,
affordable cost.

GCP offers many machine learning APIs, among which we take a look at
the 3 most popular APIs:

Cloud Speech API

A powerful API from
GCP! This enables the user to convert speech to text by using a neural network
model. This API is used to recognize over 100 languages throughout the world.
It can also support filter of unwanted noise/ content from a text, under
various types of environments. It supports context-awareness recognition,
works on any device, any platform, anywhere, including IoT. It has features like Automatic Speech Recognition (ASR), Global
Vocabulary, Streaming Recognition, Word Hints, Real-Time Audio support, Noise
Robustness, Inappropriate Content Filtering and supports for integration with
other APIs of GCP.

·Buying products and services with the
sound of your voice:Another most
popular and mainstream application of biometrics, in general, is mobile
payments. Voice recognition has also made its way into this highly competitive
arena.

·A hands-free AI assistant that knows who you are:Any mobile phone nowadays has voice recognition software in the
form of AI machine learning algorithms.

Cloud Translation API

Natural language processing (NLP) is a part of artificial intelligence that focuses on Machine Translation (MT). MT has become
the main focus of NLP group for many years. MT deals with translating text from
the source language to text in the target language. Cloud Translation API
provides a graphical user interface to translate an inputted string of a
language to targeted language, it’s highly responsive, scalable and dynamic in
nature.

This API enables
translation among 100+ languages. It also supports language detection
automatically with accuracy. It provides a feature to read a web page contents
and translate to another language, and need not be text extracted from a document.
The Translation API supports various features such as programmatic access, text
translation, language detection, continuous updates and adjustable quota, and
affordable pricing.

The following image
shows the architecture of the translation model:

In other words, the
cloud translation API is an adaptive Machine Translation Algorithm.

The most important
application of the model is the conversion of a regional language to a
foreign language.

The cost of text translation and language detection is $20 per 1
million characters.

Use cases

Now, as we have
learned about the concepts and applications of the API, let’s learn two use
cases where it has been successfully implemented:

·Rule-based Machine Translation

·Local Tissue Response to Injury and Trauma

We will discuss
each of these use cases in the following sections.

Rule-based Machine Translation

The steps to
implement rule-based Machine Translation successfully are as follows:

1.Input text

2.Parsing

3.Tokenization

4.Compare the rules to extract the meaning of prepositional phrase

5.Find word of inputted language to word of the targeted language

6.Frame the sentence of the targeted language

Local tissue response to injury and trauma

We can learn about
the Machine Translation process from the responses of a local tissue to
injuries and trauma. The human body follows a process similar to Machine
Translation when dealing with injuries. We can roughly describe the process as
follows:

1.Hemorrhaging from lesioned vessels and blood clotting

2.Blood-borne physiological components, leaking from the usually
closed sanguineous compartment, are recognized as foreign material by the
surrounding tissue since they are not tissue-specific

5.Ingrowth of blood vessels and fibroblasts, and the formation of
granulation tissue

6.Deposition of an unspecific but biocompatible type of repair
(scar) tissue by fibroblasts

Cloud Vision API

Cloud Vision API is powerful image analytic tool. It
enables the users to understand the content of an image. It helps in finding
various attributes or categories of an image, such as labels, web, text,
document, properties, safe search, and code of that image in JSON. In labels
field, there are many sub-categories like text, line, font, area, graphics,
screenshots, and points. How much area of graphics involved, text percentage,
what percentage of empty area and area covered by text, is there any image
partially or fully mapped in web are included web contents.

The document
consists of blocks of the image with detailed description, properties show that
the colors used in image is visualized. If any unwanted or inappropriate
content is removed from the image through safe search. The main features of
this API are label detection, explicit content detection, logo and landmark
detection, face detection, web detection, and to extract the text the API used Optical Character Reader (OCR) and is supported
for many languages. It does not support face recognition system.

The architecture
for the Cloud Vision API is as follows:

We can summarize
the functionalities of the API as extracting quantitative information from
images, taking the input as an image and the output as numerics and text.

The components used
in the API are:

·Client Library

·REST API

·RPC API

·OCR Language Support

·Cloud Storage

·Cloud Endpoints

Applications of the
API include:

·Industrial Robotics

·Cartography

·Geology

·Forensics and Military

·Medical and Healthcare

Cost: Free of charge for the first 1,000 units per month; after
that, pay as you go.

( This sponsored post is part of a series designed to highlight recently published Packt books about leading technologies and software applications. The opinions expressed are solely those of the author and do not represent the views of GovCloud Network, GovCloud Network Partners.)